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Development of an effective predictive screening tool for prostate cancer using the ClarityDX machine learning platform
- Source :
- npj Digital Medicine, Vol 7, Iss 1, Pp 1-11 (2024)
- Publication Year :
- 2024
- Publisher :
- Nature Portfolio, 2024.
-
Abstract
- Abstract The current prostate cancer (PCa) screen test, prostate-specific antigen (PSA), has a high sensitivity for PCa but low specificity for high-risk, clinically significant PCa (csPCa), resulting in overdiagnosis and overtreatment of non-csPCa. Early identification of csPCa while avoiding unnecessary biopsies in men with non-csPCa is challenging. We built an optimized machine learning platform (ClarityDX) and showed its utility in generating models predicting csPCa. Integrating the ClarityDX platform with blood-based biomarkers for clinically significant PCa and clinical biomarker data from a 3448-patient cohort, we developed a test to stratify patients’ risk of csPCa; called ClarityDX Prostate. When predicting high risk cancer in the validation cohort, ClarityDX Prostate showed 95% sensitivity, 35% specificity, 54% positive predictive value, and 91% negative predictive value, at a ≥ 25% threshold. Using ClarityDX Prostate at this threshold could avoid up to 35% of unnecessary prostate biopsies. ClarityDX Prostate showed higher accuracy for predicting the risk of csPCa than PSA alone and the tested model-based risk calculators. Using this test as a reflex test in men with elevated PSA levels may help patients and their healthcare providers decide if a prostate biopsy is necessary.
- Subjects :
- Computer applications to medicine. Medical informatics
R858-859.7
Subjects
Details
- Language :
- English
- ISSN :
- 23986352
- Volume :
- 7
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- npj Digital Medicine
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.32101f2e4bdf41bc810afa318fa28979
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41746-024-01167-9